Lead Scoring: Optimizing SaaS Marketing-Sales Funnel by Extracting the Best Leads with Applied Machine Learning
-
Updated
Jan 11, 2024 - Python
Lead Scoring: Optimizing SaaS Marketing-Sales Funnel by Extracting the Best Leads with Applied Machine Learning
This project predicts Customer Lifetime Value (CLV) for e-commerce. It aims at forecasting the revenue a business can expect from a customer over time. I did an explatory analysis. From Linear Regression to Neural Networks, explore how different models perform in predicting CLV.
This repository contains a project that analyzes the impact of media advertising πΊπ»π° on sales πΈ using SQL for data processing and Tableau for interactive dashboards π. The dashboard visualizes how advertising spend influences sales and helps optimize marketing ROI π.
This project examines cart abandonment trends at MagicMade e- commerce , identifying revenue loss, customer behavior, and optimization strategies. It includes key insights, data visualizations, and recommendations to improve checkout experience and boost conversions.
Add a description, image, and links to the marketing-optimization topic page so that developers can more easily learn about it.
To associate your repository with the marketing-optimization topic, visit your repo's landing page and select "manage topics."